Sarmanov Family of Bivariate Distributions for Multivariate Loss Reserving Analysis |
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Authors: | Anas Abdallah Jean-Philippe Boucher Hélène Cossette Julien Trufin |
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Institution: | 1. école d’Actuariat, Université Laval, Quebec City, Quebec, Canada;2. Département de Mathématiques, UQAM, Montreal, Quebec, Canada;3. Département de Mathématiques, Université Libre de Bruxelles (ULB), Brussels, Belgium |
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Abstract: | The correlation among multiple lines of business plays a critical role in aggregating claims and thus determining loss reserves for an insurance portfolio. We show that the Sarmanov family of bivariate distributions is a convenient choice to capture the dependencies introduced by various sources, including the common calendar year, accident year, and development period effects. The density of the bivariate Sarmanov distributions with different marginals can be expressed as a linear combination of products of independent marginal densities. This pseudo-conjugate property greatly reduces the complexity of posterior computations. In a case study, we analyze an insurance portfolio of personal and commercial auto lines from a major U.S. property-casualty insurer. |
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